Stephen Becker
Assistant Professor

Room number: ECOT 338

UPDATE: July 2019, I am moving my office from ECOT 231 to ECOT 338.

I joined the department of Applied Math in fall 2014. Previously I was a Herman Goldstine Postdoctoral fellow in Mathematical Sciences at IBM Research in Yorktown Heights, NY, and a postdoctoral fellow via the Fondation Sciences Mathématiques de Paris at Paris 6 (JLL lab), after doing my doctoral work at Caltech.

Broadly speaking, our group is interested in information extraction from various types of datasets. We are part of a hybrid field combining applied math with computer science and signal processing techniques. Some specific topics we research are:

  • Optimization: first-order methods, quasi-Newton methods, primal-dual algorithms, convex analysis.
    • Types of problems: from computational imaging, and semi-definite programs (from relaxations, or from robust PCA)
    • Mathematical applications: compressed sensing and variants, matrix completion and variants (robust PCA…), non-negative matrix factorization and end-member detection, sparse SVM
  • Numerical linear algebra: randomization and its interplay with optimization methods
  • Sampling theory: how to make the best use of your resources when confronted with big data
  • Physical applications: radar ADC using compressed sensingquantum tomography, MRI, medical imaging, IMRT, renewable energy, big-data
    • Recent applications (2015--2018) have been in super-resolution (optical) microscopy and photo-acoustic microscopy

To get a more specific idea of the research our group does, here are some topics we're doing in 2018:

  • Parametric and compressive estimation, for phase retrieval (Jessica) in x-ray imaging, and for discovering archaeological ruins (Abby) in radar imaging without creating a DEM
  • Theoretical machine learning: sub-sampling and sketching (Farhad, Eric)
  • Avoiding/analyzing saddle points in non-convex optimization: for biconvex programming in program analysis and/or controls (Jessica), and for dictionary learning and neural network learning (Leo)
  • Improving accuracy of sparse estimation using mixed-integer programming (Eric, Leo)
  • Efficient computation of the cross-ambiguity function (CAF) for signal processing, to estimate time-of-arrival of radar signals (James)
  • Randomized algorithms for numerical linear algebra and optimization (James, Derek)
  • Optimization algorithms in general, and ill-conditioning and pre-conditioning (James, Jessica, Osman)
  • Efficient algorithms for GPUs (James, Derek, Jessica)
  • Tensor decompositions (Osman, Derek)
  • Robust estimation (Richie)
  • Misc imaging applications (for optical super-resolution, with Carol Cogswell's group in ECEE; and for photo-acoustic super-resolution, with Todd Murray's group in Mech E)
  • Stochastic variance reduction methods for non-linear inverse problems
  • Remote sensing of the Chesapeake bay (Cheryl)
  • Behavior genetics (Richard, Farhad)

News

  • Plans for Summer 2019
    • Internships to be announced soon
  • Winter 2018/2019
    • Marc Thomson and Richard Border are doing their Masters theses with the group
    • Liam Madden has joined the group (working also with Emiliano Dall'Anese)
    • Richie Clancy is working on robust optimization
  • July 2018: Becker is PI on a 3-year $150k NSF grant in computational math
  • July 2018: Becker is Co-PI on Prof. Ken Jansen's ALCF project
    • This gives us early access to the new Aurora supercomputer (the nation's first exascale computer)
  • Summer 2018 activities:
  • Spring 2018: Farhad Pourkamali-Anaraki (PhD then Postdoc in the group) accepts a tenure-track professor job at U Mass Lowell's computer science deparment
  • May 2017: Farhad Pourkamali-Anaraki receives his PhD in electrical engineering
  • May 2017: Derek Driggs receives his Masters in applied math, and heads to Cambridge for his PhD
  • April 2017: Derek Driggs wins the Gates Cambridge scholarship (fully funded PhD at Cambridge, equivalent to a Rhodes scholar for Oxford)
  • Summer 2016:
  • July 2015, Becker awarded the Beal-Orchard-Hays prize
    • along with Michael Grant and Emmanuel Candes. The BOH prize is awarded every 3 years for outstanding optimization software

Websites

Our research group website has more information on research topics.

(note: there is also some interesting description of our work at our old website. The only website that we update regularly is the research group website)

Misc

For K-12 students and educators interested in partnering with CU

Some resources:

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